Neural Tangents is a library designed to enable research into infinite-width neural networks. It provides a high-level API for specifying complex and hierarchical neural network architectures. These networks can then be trained and evaluated either at finite-width as usual or in their infinite-width limit. Infinite-width networks can be trained analytically using exact Bayesian inference or using gradient descent via the Neural Tangent Kernel. Additionally, Neural Tangents provides tools to study gradient descent training dynamics of wide but finite networks in either function space or weight space. The entire library runs out-of-the-box on CPU, GPU, or TPU. All computations can be automatically distributed over multiple accelerators with near-linear scaling in the number of devices. Neural Tangents is available at www.github.com/google/neural-tangents. We also provide an accompanying interactive Colab notebook.
翻译:神经线网是一个图书馆,旨在对无限宽线神经网络进行研究,它为具体指定复杂和等级神经网络结构提供一个高级API,然后这些网络可以按通常的有限线或无限线限制进行训练和评价。无限线网可以使用精确的贝氏推论或通过神经洞心流利用梯度下降进行分析培训。此外,神经线网提供工具,用于研究功能空间或重量空间中宽但有限的网络的梯度下潜训练动态。整个图书馆都可以在CPU、GPU或TPU上运行出框。所有计算可以自动分布在设备数量上具有近线缩放的多加速器上。神经线感应可在www.github.com/google/neural-tangents上查阅。我们还提供了一个交互式的Colab笔记本。